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________________________________________________________________________ Alt, Bradley R. 2009. Business Consulting for the Transportation Industry: Using GIS Data and Tools to
Support Better Decision Making, Minnesota. Volume 11, Papers in Resource Analysis. 14 pp. Saint Mary’s
University of Minnesota University Central Services Press. Winona, MN. Retrieved (date)
http://www.gis.smumn.edu
Business Consulting for the Transportation Industry: Increasing Profitability,
Performance, and Productivity by Using GIS Data and Tools to Support Better
Decision Making
Brad Alt
Department of Resource Analysis, Saint Mary’s University of Minnesota, Winona, MN
55987
Keywords: Consulting, Transportation, Logistics, GIS, Decision Making, GPS, RFID,
Mapping
Abstract
Through the use of improved business processes and the support of GIS tools, companies
can increase revenue, decrease time to make better decisions and use GIS technologies to
replace underperforming processes. In the trucking industry, technology has been used
for many purposes including communication, mapping, planning, and reporting. This
project compares the effectiveness of new logistics technologies to old techniques that
typically used more man hours to complete similar tasks. The process and resulting
recommendations are supported by companies that saw a 30% increase in the number of
trucks managed compared to the number workers assigned to manage them, decreases in
key areas that caused companies to lose revenue and provided improvement in asset
utilization. The results of each case study varied, but in each case, significant
improvements were made in how the customer processed data or eliminated hours of data
entry. The study and recommendations provided ways to analyze business needs, set
achievable goals, and ways to improve an organization.
Introduction
“The Motor Carrier Act of 1980 partially
deregulated the trucking industry,
dramatically increasing the number of
trucking companies in operation”
(United States Department of
Transportation, 2002). The deregulation
of any industry causes competition to
increase and the trucking industry was
no exception. The competition among
trucking companies led each company
striving for more profits through
competitive advantage. Competitive
advantage, as defined at Investor Guide
(2009), is “a condition which enables a
company to operate in a more efficient
or otherwise higher-quality manner than
the companies it competes with, and
which results in benefits accruing to that
company.” The trucking industry
involves shipping one company’s
product on another company’s truck. To
be competitive, the owner of the trucks
(carrier) must find ways to price their
deliveries, track their assets such as
trucks and trailers, and deliver the
customer product on time better than
their competition. Without
advancements in technology, decisions
were made on hunches or hours of
analyzing spreadsheets of data to
2
determine the best process to increase
revenue. Trucking companies used
manual methods, requiring paper and
pencil or multiple spreadsheets, for
years. However, the introduction of
computers and software specifically
designed for the trucking industry has
allowed for more efficient and practical
methods of management to occur. The
historic generation of trucking
companies used magnetic boards and
erasable chalk to diagram processes of
transportation. Communication was
limited to two way radios and the
drivers’ honesty of his/her location. The
variables of competition were limited.
To gain competitive advantages over
other companies, software was
developed to increase the visibility of
trucks while in-transit to a customer
location, process more data with less
employees and make better business
decisions with information stored in
databases.
Trucking companies embracing
technology to gain a competitive
advantage use tools such as logistics
software, Geographic Information
Systems (GIS), Radio Frequency
Identification (RFID) readers, and
Global Positioning Satellite (GPS). GIS
was used in the transportation industry
since the late 1980’s when some
companies including Schneider National,
the first to sign a contract, started using
Qualcomm units in their trucks.
Qualcomm was originally installed as an
onboard communication device that
allowed communication with the
dispatcher. This provided opportunities
for better delivery route tracking and
communication between the drivers and
carriers shipping products. Since the
1980’s, spatial data has become more
prevalent and is growing in part due to
the enhanced data collection via devices
such as sensors, satellites, RFID readers,
and GPS enabled devices. 80% of
business data has potential to be geo-
referenced, i.e. have spatial location
attached (Bossler, 2002). In the
transportation industry, there is a
plethora of geo-referenced data to be
analyzed, which can support clear and
profitable decision making. GIS tools are
utilized to support these decisions and
provide the decision in a timely manner.
In this study, four trucking
companies were analyzed to measure the
effectiveness of logistics technologies
compared to old techniques that
typically used more man hours to
complete similar tasks. Logistics is
defined by the Business Dictionary
(2009) as “Planning, execution and
control of the procurement, movement,
and stationing of personnel, material,
and other resources to achieve the
objectives of a campaign, plan, project,
or strategy.” Four case studies were used
to evaluate implementation logistics
techniques at each company and to
analyze how effectively they were
utilizing technology. Recommendations
were provided regarding how technology
can be utilized to gain competitive
advantage.
Methods
A good strategy is based on meeting the
business needs of the organization
(Douglas, 2008). To meet the needs of
an organization, the needs must be
understood. The methodology used to
evaluate the organizations researched in
the following case studies was broken
down into four phases.
Assessment
Auditing
Implementing Change
Evaluating Results
3
Assessment
The assessment phase was the most
important step in understanding the
organization because the information
gathered was the basis for which future
recommendations would be made. The
goal of the assessment phase was to
measure and identify areas for
organizational improvement. To identify
improvement over a period of time a
baseline performance must be
established. After the baseline is
measured, the opportunities for
improvement are found by comparing
the baseline to comparison baselines.
Opportunity is defined as a metric that is
not performing well compared to
benchmarks of other optimized
companies. Selected areas of opportunity
were chosen to focus on and a current
state model was created. According to
The Bridgefield Group (2006), current
state is defined as the review process to
determine current status of a system or
process that defines its inputs, data flow
and outputs and provides the starting
point for identifying changes required to
reach a desired future state. This is also
referred to by the “As-Is” state. To find
the areas for improvement, benchmark
metrics were used. Benchmarks were
found by generating a list of metrics
commonly used by comparable
companies. The metrics were compared
and measured against the researched
companies. Common metrics included
percentage of average non-revenue
generating miles, the number of
deliveries completed per customer and
revenue per delivery. The metrics were
designed specifically to measure
business drivers in the transportation
industry that equate to profitability,
performance, and productivity. The data
elements provided a base line to begin
pre and post evaluation of businesses
performance indicators. For a full list of
metrics please refer to Appendix A. In
this list, areas in need of improvement,
highlighted in red or yellow, were
discussed with each organization and
were later used to measure success.
Biographical data was also captured to
compare the processing speed of
employees to their job functions.
Biographical data can be found in
Appendix B.
Auditing
The auditing phase was performed to
provide the understanding of current
procedures of each organization’s
software architecture along with data
flow. This is referred to as a company’s
current state. This is displayed in Figure
1. Bottlenecks, events that decreased
productivity, in the data flow accounted
for hours of time spent on manual tasks
where the process was dependent on a
human task to be completed before
another task could be started. Manual
processes were identified in Figure 1 as
dashed lines connecting two tasks. As-Is
reviews were consistently the most
beneficial task completed because this
provided information related to data
flow. It also provided areas of
improvement that were commonly fixed
by use of software applications with
spatial components to automate manual
procedures or providing web
applications with map features to
disseminate data more quickly.
Examples of automated procedures and
GIS tools are discussed in the Analysis
section where it was found that the
coupling of technology and GIS would
provide benefits.
Another part of the auditing
phase was to review the organization
4
Figure 1. Microsoft Visio files displaying current
state workflow. Dashed lines represent manual
processes between tasks. Solid lines represent
automated tasks performed by employees.
business practices and existing software.
Employees of the researched companies
were interviewed and the information
was used to gain insight into business
processes and software technologies.
The answers provided in the interviews
were compared against the
organization’s strategic goals and
objectives to ensure the software was
optimally designed. Performance
indicators such as the number of
dispatchers compared to the number of
managed drivers, average number of
phone calls per order and percentage of
average non-revenue generating miles
were evaluated to identify improvements
as either a technology-based tool, such
as GIS based map, or process-based
improvements that would change the
current procedures. The indicators were
measured against the benchmark
companies that have effectively utilized
techniques and technology capabilities
(Figure 2). Figure 2 has a white section
in the middle representing the software
tools being used. The maroon section
represents software technology that was
available to the organization but was not
being utilized efficiently. Each label
represents a task that was performed by
employees of the customer being
analyzed or important criteria by which
they are measured.
Figure 2. Graphical representation of software
tools compared between the researched
organization and an organization that is
optimally performing.
Implementing Change
After establishing the goals of each
organization researched for this project,
a set of achievable improvement tasks
were identified. Recommendations were
provided in the form of future state
process flows to graphically present how
the process was altered from the current
state. Future state process flows are
representations of the how the current
defined process will be altered after
recommended changes have been
implemented. The future state accounted
for areas that increased profitability,
performance, or productivity.
The process of implementing the
recommendations utilized project
management skills and techniques for
change management. To implement new
process changes, training was provided
to ensure each employee understood the
expectations and how the solution
improved the process. Resistance to
change, inadequate sponsorship, and
5
unrealistic expectations were found to be
problems during organizational research
for this project.
Evaluating Results
After changes were implemented to each
organization, the final step was to
measure the results. This was done by
re-evaluating the data elements, such as
the performance indicators, biographical
data, and comparing pre-engagement
and post engagement figures. The most
common metrics included percentage of
average non-revenue generating miles,
the number of deliveries completed per
customer and revenue per delivery. The
recommendations were measured to
determine if they had the desired effect
on the organization over a period of
time. The desired changes were
increased revenue, decreased empty
miles, and increased visibility of trucks
on the road. If the results were positive
the project was considered a success.
Analysis
Through the use of change
methodologies described earlier, change
was implemented to each company for
the following reasons:
Organization 1: Analysis found that
a large percentage of deliveries had
non-revenue generating miles that
could be eliminated by implementing
a mobile communication system
which tracked movement of trucks
across the country and provided
enhanced communication with
dependent personnel.
Organization 2: Through interviews
with management it was found that
important products being delivered
by a trucking company were not
being managed properly. The
process was failing due to a lack of
visibility of the trucks and this data
being kept in multiple spreadsheets.
The data was not shared among
employees and time was spent
tracking down information for the
shipping customer’s product.
Organization 3: Customers sighted
lack of control over the amount miles
being driven outside of the
anticipated route. The extra miles
driven were reducing the revenue
associated with product being
shipped, increasing the amount of
wear on the vehicles, and using more
fuel than necessary to deliver the
product.
Organization 4: Customers indicated
the number of employees being used
to enter data, call shipping
companies for delivery
appointments, and communication
with truck drivers was increasing due
to growing size of the researched
company.
During the auditing phase of
Organization 1, which was part of the
initial phase of analysis, the standard
operating procedure of the organization
was found to be causing excessive non-
revenue generating miles. It was found
that dispatchers, whose job is to assign a
driver to an order that is being delivered,
did not know when a truck was available
or how far they were from the next
available load. Another issue related to
the auditing process found drivers must
call into the dispatch office to report
their position and also when drivers
delivered a load. The procedures were
not efficient and provided inaccurate
data. This caused inconsistent data used
to pre-plan drivers and also caused more
manual data entry than was necessary to
complete the job function. The solution
6
for the issues was to use multiple GIS
tools including mobile communications,
mapping tools, and a reporting tool to
dissect poorly planned resources. Mobile
communications utilized GPS to
send/retrieve data, such as reference
numbers, weight, truck number, and
trailer numbers without the need for
manual data entry. The tool prevented
the need to call back to the dispatch
office, therefore saving time and
providing customer data quickly and
efficiently. The GPS positions were geo-
referenced at multiple points in the
process then the route could be further
understood and became more
predictable. The predictable route
provided dispatchers the ability to make
qualified decisions about which
available truck was closest to the
available order. The position reports also
allowed the ability to plot truck positions
on maps and to view the trucks on a
digitally displayed map (Figure 3).
Figure 3. Map plots available loads versus trucks
on map using ALK’s PC Miler mapping
software.
Through interviews with senior
leadership at Organization 2, it was
identified that tracking high priority
loads had resulted in lost revenue and
lower customer satisfaction. The
customer provided high value freight
with an emphasis of on-time delivery but
had lost valuable revenue dollars due to
the inability to track where the trucks
were and when they were running late.
After evaluation, it was decided a web
portal with a spatial component would
be implemented to address the concern
of limited tracking of trucks. The web
portal increased visibility of data for
reporting purposes. It also provided
dispatchers with the ability to track the
identified loads and highlighted late
delivery trucks. As seen in Appendix A,
trucks were highlighted with green,
yellow, and red dots indicating if they
are on time (green), may be late (yellow)
or are running late (red). In addition to
the red indicator, an email notification
was sent to the dispatcher and customer
to indicate the product would not be
delivered on-time. The external
customer (the customer receiving the
product) also had the ability to login to
the portal to find the location of the
delivery truck and the estimated time of
arrival to their warehouse. The portal
eliminated phone calls to dispatch from
customers and enabled the external
customers to get information quickly.
The tool helped share information with
end-users and management, thus
providing a better understanding of the
data in the system. The spatial feature of
the web portal was used to graphically
display information over the web. The
resulting web portal (Figure 4) shows
truck positions, available orders on a
map, the number of available trucks by
regional designation, and can also
provide revenue and cost data.
The case study at Organization 3
revealed issues regarding trucks routed
mileages and finding the best
coordinated and efficient routes. To find
out of route miles, a calculation was
used by comparing the mileage of truck
odometers to the estimated mileage of
the route found using routing software.
7
Figure 4. Web portal with spatial features
displaying high priority load information. Color
coordinated dots indicated if product is on-time.
The organization research found trips
included out of route mileage. It was
determined a solution must be provided
to decrease the number of miles being
driven that are not associated with the
actual delivery of a customer’s product.
This issue was discovered by using the
initial metrics and was further analyzed
by interviews with dispatchers during
the auditing phase. The product being
delivered had routes that were estimated
to travel on roads equaling an anticipated
number of miles. Without a process to
track the position of the truck, the driver
traveled on any route that he/she chose.
The result was excessive wear on the
vehicle, more fuel consumption and
delays on the product being delivered.
During the implementation phase, a web
application with a mapping tool was
introduced to eliminate out of route
mileage that a truck driver may incur by
taking the wrong roads not provided by
the logistics software. A mobile
communication solution was also
implemented that tracked GPS positions
and reported out of route mileage to
dispatchers. After the delivery was
completed, a dispatcher or manager used
the maps to plot suggested routes versus
actual completed routes based on GPS
data collected along the trip. Figure 5
shows the plotted route from the
dispatcher compared to the actual route
driven.
Figure 5. Plot route versus actual. Blue line
represents actual route, Green line represents
dispatched route.
In the auditing phase of
Organization 4, it was discovered that a
trucking company had problems keeping
track of vehicles that were being shipped
from a processing facility to the
automotive dealerships. The current
process relied on data collected from
drivers after the delivery was made. The
automotive dealerships could not depend
on estimated times of arrival and
expensive cars were being transported
without a proficient method of tracking.
The gap in the existing technology was
filled by using Radio Frequency
Identification and bar codes on vehicles
to save time on order management,
provide GPS data and set estimated
times of arrivals for dealerships
expecting the new vehicles for delivery.
Further problems were discovered
during the audit phase of Organization 4.
The issue was that hours were being
spent by in-house staff updating orders
after the driver completed the delivery.
The process would involve a minimum
of three phones calls from the carrier and
then another three to five minutes of
updating in the software. The solution
Actual route
Dispatched route
8
utilized technology and process
improvements and used RFID
technology to integrate the scanning of
vehicles as they passed the gates from
the origin and again when they made it
to the entrance gate of the final location.
RFID readers and GPS enabled devices
were the solution. The solution allowed
the customer to take data that was
collected via the RFID readers and
electronically import the information to
the logistics software. The RFID reader
updated the customer order each time it
was scanned. This eliminated the need
for phone calls or manual updates of
order data, therefore reducing workload
and gaining efficiency in the order
processing, and more accurate tracking
of vehicle deliveries.
Findings
During the assessment and auditing
phases, it was discovered that all four
companies benefited from improved
processes and all are now using
technology to improve the business’s
profitability, performance, and
productivity. The organizations
researched use these technologies to
increase revenue, improve asset planning
skills, gain better sales forecasting,
improve on-time delivery percentages,
and perform improved analysis on their
data. The methods and tools that each
organization utilized are different due to
a number of factors. Those factors could
be the business niche they are in, the
level to which technology has been
introduced to the company. Companies
were able to increase profitability by
limiting the number of non-revenue
generating miles and eliminating out of
route miles. As seen in Appendix B,
companies that were able to change
current processes in favor of utilizing
technologies, such as RFID, were able to
decrease the number of phone calls per
day and increase the productivity of
staff. This data was indicative of
qualitative changes that can affect the
overall happiness of employees. The
overall effect may actually improve
employee morale and hopefully result in
fewer turnovers. Companies that utilized
GIS tools and logistics software were
able to keep employee numbers the same
while increasing the number of managed
trucks by over 30%.
The results of the case study at
Organization 1 included decreased
empty miles associated with the
order that negatively affects profit,
increased revenue per mile,
increased the ability of users to
provide accurate and timely
information regarding the customer’s
order, availability of resources or
status while in-transit, and decreased
manual processes to update load
information in the database. Data
provided in Appendix C.
The benefits provided by the solution
implemented at Organization 2 was
real-time data sharing, ability to
track and report on high priority
freight, and automated notification to
customers with interest in the load’s
delivery time. The solution improved
performance and productivity by
decreasing time spent
communicating with customers. In
addition, the solution provided
increased ability for better decision
making and data was based on real-
time information.
For the real-time solution provided
to Organization 3, reports were
created and triggered to send out
email notifications that alerted
dispatchers when the acceptable
9
tolerance of out of route miles had
been broken.
The evaluation of the customer issue
and recommendations provided to
Organization 4 increased
profitability due to fewer hours used
to input data, increased productivity
due to not taking excessive phone
calls and improved performance by
drivers not have to report arrival and
departure times after each pickup or
delivery. The three phone calls per
order were reduced to zero and the
manual updates were eliminated due
to information updates provided
electronically.
All of the organizations benefited
from enhancements in the visibility of
trucks through the use of mobile
communications. This was likely due to
less time taken to find a truck’s location
and having data that is constantly
updated allowed companies to quickly
report on arrival or departure data. It was
also found that when software tools were
used to enhance the decision making
process companies typically see empty
mileage percentages decreased, revenue
per miles increased and out of route
miles decreased. Results indicated
companies using mobile communication
realized a decrease in 5% of empty miles
for the months following
recommendations from this project. The
limitations of the analysis are the
variables, including economic
circumstances that could have increased
the revenue with or without the
recommendations and employee
performance. It is difficult to evaluate
the skill level or ability of an employee
to make a decision. The improvements
in key areas could be attributed to
training or provided technologies but
also could have been the normal learning
curve of the employee to their job.
Without the training, they may still have
made better decisions thus increasing
revenue and decreasing empty mileage.
It is apparent the increased
utilization of technology will decrease
manual dependencies, such as tabular
data or manual documentation. This use
of software and company specific
recommendations allowed the
organizations to leverage the tools that
allow for better decision making such as
sharing information that is stored
centrally and communicated globally.
The amount of time it takes to generate
sales forecasting data and revenue
reports were not specifically measured,
but were significantly decreased. This is
likely due to information being stored in
one database and the automation of
reports to pull specific information on a
scheduled basis.
The significance of finding areas
for improvement can be measured by
operational metrics, increased revenue,
employee satisfaction and overall
reduction in the use of manual
techniques.
Customer projects such as the
ones identified in this report are
successful or failures due to many
factors. Some common reasons for
failure include:
1. Senior Management buy-in is not
secured.
2. Limited user involvement in the
planning stages.
3. Inadequate upfront planning or
communication.
The same is true for why projects
succeed and include:
1. Benefits can be measureable and
common goals are established.
2. Focus is on users.
10
3. Executive sponsor the project
through to the end.
Additional limitation put on
process improvement can be from
existing employees unwilling to provide
accurate representation of their duties or
company cultures that do not promote
change. Technology enabled solutions
may increase profitability and
productivity but a management staff that
does not understand the value of
promoting the need to change or how to
manage the change can impede the
performance of the employee. The most
significant limitation is the executive
level sponsorship of the project. Without
the continued support and leadership
from management, end users typically
resist any change that may negatively
affect their day to day duties.
Conclusions
This project was developed to measure
the effectiveness of new logistics
technologies compared to old techniques
that typically used more man hours to
complete similar tasks. The result of the
research and analysis provided ways that
any company can evaluate their own
processes and measure the effectiveness
of changing from antiquated habits to
embracing technology for purposes of
profitability, performance, and
productivity. The use of GIS tools and
software technologies improves the
profitability, productivity and
performance of trucking companies.
Case studies in the research were
evaluated and the analysis supports
recommendations made to clients
regarding how technology is utilized to
gain competitive advantage. The result
of the research and analysis provides
ways that any company can evaluate
their own processes and improve their
performance by introducing
technological advances in the trucking
industry. The project has provided a
deeper understanding of the advantages
in utilizing software technology.
Information gained from this project will
be used to further analyze existing trends
in technology and as a basis for
company comparisons.
Acknowledgements
I would like to thank John Ebert of the
Department of Resource Analysis staff
at Saint Mary’s University of Minnesota
for his guidance throughout this process.
I would also like to thank Dr. David
McConville for his direction when I
entered the program. The support of my
family has also been appreciated during
the audit phase of my research.
References
Bossler, J. D. 2002. An Introduction to
Geospatial Science and Technology,
Manual of Geospatial Science and
Technology.
Business Dictionary. 2009 Retrieved on
October 22, 2009 from www.
businessdictionary.com.
The Bridgefield Group. 2006.
Bridgefield Group ERP/Supply chain
Glossary. Retrieved on October 22,
2009 from
www.bridgefieldgroup.com.
Douglas, B. 2008. Achieving Business
Success with GIS.
Investor Guide. 2009. Investor Words
Dictionary. Retrieved on October 22,
2009 from www.investorwords.com.
United States Department of
Transportation. 2002. Federal Highway
Administration. "The Freight Story: A
National Perspective on Enhancing
11
Freight Transportation." Retrieved on
October 22, 2009 from http://www.
ops.fhwa.dot.gov/freight/freight_analys
is/freight_story/freight.pdf.
12
Appendix A. Key performance data found by using excel macros with SQL code to pull specific metric
data from the SQL database. The information is used to measure productivity and performance statistics.
Version 2008.07_08.0981 Invoice Selection Entries 3
Active Tractor Count 168 Total Invoices 45570
Active Chargetypes 14
% Active Chargetypes with GL# 100.00%
Users Entered 100 Miscellaneous Invoices 55
Groups Entered 16 Supplemental Invoices 418
% Users To Groups 83.00% Printed Invoices 45269
Transferred Invoices 45263
Master Bills Printed 0
% Cities With Valid Region 1 8.93% Invoices Created Last 30 Days 1725
Total Companies 72409 Invoices Created Last 90 Days 4836
Non Imported Companies 72409 Credit Memo/Rebills 3182
Companies with Missing/Incomplete Zip 1013 % Invoices With Accessorial 31.96%
Active Bill To Companies 58100 % Auto Rated Invoices 0.02%
Ship or Cons Without Directions 61859
Active Drivers 169
Drivers Manually Entered 654 Pay Header Count 22021
AP Drivers 0 Future Pay Periods 35
AP Drivers with No PayTo 0 Settlement Schedules 4
Active Tractors 168 Transferred Pay Headers 21273
Tractors Manually Entered 523 Closed Pay Headers 745
Payroll Tractors 0 Active Paytypes 48
AP Tractors with No PayTo 17 % Active Paytypes with GL# 100.00%
Active Trailers 858 Payable Drivers with No Activity Table 0
Active Pay To's 4039 Payable Tractors with No Activity Table 0
Orphaned PayTo's 54 Payable Carriers with No Activity Table 1
Active Carriers 3565 Standing Deductions 381
Carriers with No Acct Type 0 Pay Details from Standing Deductions 8
GLReset Entries 14 Resources with Standing Deduction 305
Pay Details with No GL 13392 % AP Tractors >1 Closed Pay Header 86.06%
Inv Details with No GL 254 % PR Drivers >1 Closed Pay Header 10.53%
% Auto Rated Trips 69.89%
% CMP Trips With a LH Pay Detail 94.40%
Total Orders 44982
Completed Orders 42179
Non Completed Active Orders 220 Billing
Copied Orders 3570 Primary Billing Rates 5
Non Copied Orders 41412 Accessorial Billing Rates 4
Non Copied Last 30 days 1361 Line Item Billing Rates 1
Non Copied Last 90 days 4165 % Acc/Linked LI with Attached Primary 100.00%
Master Orders 29 Billing Rates Used 2
Orders Copied From Master 189
Users Creating > 20 Non-Copied Orders 39 Pay
Imported Orders 0 Primary Pay Rates 16
% Pre-rated Orders 0.03% Accessorial Pay Rates 8
Line Item Pay Rates 0
% Acc Pay Rates with Attached Primary 100.00%
Split Trips 9322 Pay Rates Used 22
X Dock Moves 486
Standalone MT Moves 471
% Moves With 1 Or More MT Events 64.83% Fuel Cards Set Up 1450
Driver Beams 4618 Account Codes Set Up 1
Tractor Beams 4311 Customer Codes Set Up 3
Trailer Beams 17687 Payable Tractors Without Cards 72
Trip Views on Pln Worksheet 20 Payable Drivers Without Cards 67
Resource Views on Pln Worksheet 20 Cards With No Asset 0
Regions Schemes Setup 4 Fuel Purchases 51585
% Trips w/Valid Org Reg1 14.65% Fuel Purchased Pay Details 87745
Consolidated Moves 809 Cash Advance Pay Details 11676
% Drivers Utilized 94.65%
% Tractors Utilized 96.37%
% Trailers Utilized 94.18%
Orders with Carrier Assigned 10094
% Trips with Calculated Mileage 99.41%
Legs with >1 Payable Resource 18181
Legs with No Payable Resource 46
File Maintenance
Order Entry
Rating
Fuel Import
Dispatch
Settlements
System Admin
TMW Suite Invoicing
13
Appendix B. Biographical data of each organization that is being analyzed. The benchmarking data was
compared against other companies and used to create ratios for performance statistics.
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Appendix C. Tabular revenue and mileage data collected prior to the case study and after the recommended
changes were implemented.
Start Year 2008
Total Total Total Total Empty Empty Empty Empty Deadhead Deadhead Deadhead Deadhead
Revenue Revenue Revenue Revenue Miles Miles Miles Miles Miles Miles Miles Miles Percent Percent Percent Percent
2008 2009 2010 2011 2008 2009 2010 2011 2008 2009 2010 2010 2008 2009 2010 2011
Jan $2,135,840 $2,021,169 1,425,284 1,613,076 95,984 117,985 6.73% 7.31% 0.00% 0.00%
Feb $2,176,684 $2,171,571 1,469,550 1,864,990 108,573 108,197 7.39% 5.80% 0.00% 0.00%
Mar $2,379,526 $2,698,724 1,584,560 2,221,329 105,543 142,797 6.66% 6.43% 0.00% 0.00%
Apr $2,170,166 $2,657,302 1,425,571 2,153,517 106,620 149,279 7.48% 6.93% 0.00% 0.00%
May $2,528,826 $2,752,936 1,592,671 2,232,238 113,198 153,004 7.11% 6.85% 0.00% 0.00%
Jun $2,712,148 $2,016,556 1,618,693 1,585,074 133,730 109,392 8.26% 6.90% 0.00% 0.00%
Jul $2,504,571 1,451,678 154,315 10.63% 0.00% 0.00% 0.00%
Aug $2,516,144 1,509,505 183,964 12.19% 0.00% 0.00% 0.00%
Sep $2,853,523 1,681,738 166,343 9.89% 0.00% 0.00% 0.00%
Oct $2,710,557 1,668,880 173,677 10.41% 0.00% 0.00% 0.00%
Nov $2,282,844 1,463,669 131,785 9.00% 0.00% 0.00% 0.00%
Dec $2,373,334 1,635,556 123,186 7.53% 0.00% 0.00% 0.00%
Total $29,344,163 $14,318,258 $0 $0 18,527,355 11,670,224 0 0 1,596,918 780,654 0 0 8.62% 6.69% 0.00% 0.00%
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